Qian Long, Hu Chuanxian, Fan Mengtao, Ji Zhuqing
Long Qian Department of Cardiothoracic Surgery, The Affiliated Huai'an 1st People's Hospital of Nanjing Medical University, Huaian, Jiangsu Province 223300, P.R. China.
Chuanxian Hu Department of Cardiothoracic Surgery, The Affiliated Huai'an 1st People's Hospital of Nanjing Medical University, Huaian, Jiangsu Province 223300, P.R. China.
Pak J Med Sci. 2025 Jan;41(1):9-14. doi: 10.12669/pjms.41.1.11087.
To explore the risk factors associated with postoperative atrial fibrillation (POAF) after off-pump coronary artery bypass grafting (OPCABG) and to construct a nomogram predictive model.
In this retrospective cohort study, clinical data of 193 patients who received OPCABG in Huai'an First People's Hospital Affiliated to Nanjing Medical University from June 2021 to November 2023 were retrospectively analyzed. Based on the established diagnosis of POAF, patients were divided into the POAF group (n=75) and the non-POAF group (n=118). Logistic regression analysis was used to screen for risk factors for POAF after OPCABG. A nomogram prediction model for POAF after OPCABG was constructed based on the independent risk factors, and the model was validated by calibration curve and the area under the receiver operating characteristic curve (AUC).
The incidence of POAF after OPCABG in the cohort was 38.86% (75/193). Age, diabetes, history of percutaneous coronary intervention (PCI), duration of operation, length of hospital stay and () were identified as independent risk factors for POAF after OPCABG (<0.05). The concordance index of the nomogram model for predicting the risk of after POAF after OPCABG based on the six independent risk factors was 0.820. The correction curve tended towards the ideal curve, and the area under the receiver operating characteristic curve was 0.820 (95% CI:0.758~0 882).
Age, diabetes, history of PCI, duration of operation, length of hospital stay and LVEF are independent risk factors for POAF after OPCABG. The constructed nomogram model has a good predictive performance for predicting POAF in patients after OPCABG.
探讨非体外循环冠状动脉搭桥术（OPCABG）后发生术后心房颤动（POAF）的相关危险因素，并构建列线图预测模型。
在这项回顾性队列研究中，对2021年6月至2023年11月在南京医科大学附属淮安第一人民医院接受OPCABG的193例患者的临床资料进行回顾性分析。根据POAF的既定诊断，将患者分为POAF组（n = 75）和非POAF组（n = 118）。采用Logistic回归分析筛选OPCABG后POAF的危险因素。基于独立危险因素构建OPCABG后POAF的列线图预测模型，并通过校准曲线和受试者工作特征曲线下面积（AUC）对模型进行验证。
该队列中OPCABG后POAF的发生率为38.86%（75/193）。年龄、糖尿病、经皮冠状动脉介入治疗（PCI）史、手术时间、住院时间和（左心室射血分数）被确定为OPCABG后POAF的独立危险因素（<0.05）。基于六个独立危险因素预测OPCABG后POAF风险的列线图模型的一致性指数为0.820。校正曲线趋向于理想曲线，受试者工作特征曲线下面积为0.820（95%CI：0.758~0.882）。
年龄、糖尿病、PCI史、手术时间、住院时间和左心室射血分数是OPCABG后POAF的独立危险因素。构建的列线图模型对预测OPCABG术后患者的POAF具有良好的预测性能。
